Shapefinders: a new morphological discriminator for large-scale structure

Astronomy and Astrophysics – Astrophysics

Scientific paper

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Scientific paper

There is a growing consesus that one must look for discriminators other than the two-point correlation function to characterise the distribution of matter in the Universe. The morphology of structure is interesting in its own right and additionally it is a characteristic that carries some memory of initial conditions and is therefore a powerful tool to study and discriminate structure formation models. In this work we propose a new diagnostic, called Shapefinders, to quantify the morphology of structure. Unlike conventional shape statistics that are based on simple ellipsoid fitting, Shapefinders arise from simple geometrical considerations and are derived from fundamental properties of a structure such as its volume, surface area, integrated mean curvature and connectivity characterised by the genus. These Shapefinders could be used to diagnose the presence of filaments, pancakes and ribbons in large-scale structure. Their lower-dimensional analogues are useful in the study of two-dimensional distributions such as temperature maps of the cosmic microwave background.

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